mcp-costco

track_order

Check delivery status for Costco orders by entering your order number to monitor shipment progress and estimated arrival times.

Instructions

Track a Costco order delivery status

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "order_number": "<order_number>"
    },
    "name": "track_order"
  }
}

Input Schema

Name	Required	Description	Default
`order_number`	Yes	Costco order number

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 11, 2026

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure but only states what the tool does without additional context. It doesn't mention whether this is a read-only operation, requires authentication, has rate limits, or what the output looks like (e.g., status details, estimated delivery time). This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose with zero waste. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned (e.g., delivery status, tracking number, updates) or behavioral aspects like error handling. For a tool with no structured data beyond the input schema, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the single parameter 'order_number' clearly documented as 'Costco order number'. The description adds no extra meaning beyond this, such as format examples or constraints, but the schema does the heavy lifting, justifying the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('track') and resource ('Costco order delivery status'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_orders' or 'status', which might have overlapping functionality, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_orders' or 'status'. It lacks context about prerequisites (e.g., whether login is required) or exclusions, leaving the agent to infer usage based on the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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